require(magrittr)
require(knitr)
require(dplyr)
require(tidyr)
require(tibble)
require(ggplot2)
require(Seurat)
require(cowplot)
require(readr)
require(readxl)
require(patchwork)
require(Nebulosa)
require(clusterProfiler)
require(ggupset)
require(pals)
parent.directory <- "external_data/"
figure_directory <- "figures/"
dir.create(figure_directory)
rerun_analysis <- FALSE
feature_size <- 6
We download the data from ArrayExpress
tonsil_bcells <- readRDS(paste0(parent.directory, "EMTAB9005/data/SEURAT_OBJECTS/HumanTonsil_BCells_scRNA_SeuratObject.rds"))
tonsil_membcells <- readRDS(paste0(parent.directory, "EMTAB9005/data/SEURAT_OBJECTS/HumanTonsil_MemoryBCells_scRNA_SeuratObject.rds"))
DimPlot(tonsil_bcells, label = TRUE, repel = TRUE, reduction = "umap")
VlnPlot(tonsil_bcells, features = c("CCL4", "CCL3"), ncol = 2, pt.size = 0.1)
VlnPlot(tonsil_bcells, features = c("MYC", "MIR155HG"), ncol = 2, pt.size = 0.01)
VlnPlot(tonsil_bcells, features = c("RASSF6", "BCL6"), ncol = 2, pt.size = 0.01)
VlnPlot(tonsil_bcells, features = c("LGALS1", "LGALS3"), ncol = 2, pt.size = 0.01)
figs8 <- VlnPlot(tonsil_bcells, features = c("CCL4", "CCL3"), ncol = 2, pt.size = 0.1)
pdf(file = paste0(figure_directory, "FigureS8.pdf"), width = 16, height = 8)
figs8&xlab(NULL)
dev.off()
## quartz_off_screen
## 2